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Bin3C: exploiting Hi-C sequencing data to accurately resolve metagenome-assembled genomes.


ABSTRACT: Most microbes cannot be easily cultured, and metagenomics provides a means to study them. Current techniques aim to resolve individual genomes from metagenomes, so-called metagenome-assembled genomes (MAGs). Leading approaches depend upon time series or transect studies, the efficacy of which is a function of community complexity, target abundance, and sequencing depth. We describe an unsupervised method that exploits the hierarchical nature of Hi-C interaction rates to resolve MAGs using a single time point. We validate the method and directly compare against a recently announced proprietary service, ProxiMeta. bin3C is an open-source pipeline and makes use of the Infomap clustering algorithm ( https://github.com/cerebis/bin3C ).

SUBMITTER: DeMaere MZ 

PROVIDER: S-EPMC6391755 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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bin3C: exploiting Hi-C sequencing data to accurately resolve metagenome-assembled genomes.

DeMaere Matthew Z MZ   Darling Aaron E AE  

Genome biology 20190226 1


Most microbes cannot be easily cultured, and metagenomics provides a means to study them. Current techniques aim to resolve individual genomes from metagenomes, so-called metagenome-assembled genomes (MAGs). Leading approaches depend upon time series or transect studies, the efficacy of which is a function of community complexity, target abundance, and sequencing depth. We describe an unsupervised method that exploits the hierarchical nature of Hi-C interaction rates to resolve MAGs using a sing  ...[more]

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